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Big Data Testing Jobs (NOW HIRING)

1 point system

QA Engineer (Data)

Fort Mill, SC · Remote

$30/hr

Some background in PySpark or Hadoop based data testing would be a big plus for us. A background mostly on the web and mobile automation side, won't be a great right fit for this role. If you can ...

EROS Technologies Inc

Big Data Developer

Mooresville, NC · On-site

$50.25 - $65/hr

They are seeking a Big Data Developer to code, test, and analyze application software while ... Responsibilities : • Coding, testing and analyzing application software • Improve existing code ...

TriOptus LLC

Big Data Engineer

Houston, TX · On-site

$53.25 - $70.50/hr

Software Engineer (Big Data) Duration: 3-6 Months CTH Location: Houston/Plano , TX This is a W2 ... testing, deployment, maintenance and improvement of software. Anthony Kay

NAVA Software Solutions

Big Data Engineer

Atlanta, GA · On-site

$53.50 - $71/hr

... building, testing, and optimizing 'Big Data' data ingestion pipelines, architectures, and data sets * 2+ years of experience with Python (and/or Scala) and PySpark/Scala-Spark * 3+ years of ...

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How much do big data testing jobs pay per hour?

As of Jul 20, 2026, the average hourly pay for big data testing in the United States is $62.98, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $70.91 per hour, depending on experience, location, and employer.

What is Big Data Testing?

Big Data Testing is the process of verifying and validating the quality, accuracy, and reliability of large and complex data sets and the systems that process them. It involves testing data ingestion, processing, storage, and retrieval to ensure that big data applications function as expected. This type of testing also checks for data integrity, performance, and scalability issues in big data environments such as Hadoop, Spark, or NoSQL databases. The goal is to ensure that data-driven applications deliver correct and meaningful insights.

What is a big data tester?

A big data tester is a professional responsible for verifying the accuracy, performance, and reliability of large-scale data systems. They use tools like Hadoop, Spark, and SQL to identify data inconsistencies, bugs, and system issues, ensuring data quality and system efficiency in environments that handle vast amounts of information.

What is the difference between Big Data Testing vs Data Analyst?

AspectBig Data TestingData Analyst
Required SkillsData validation, scripting, understanding of big data toolsData interpretation, SQL, visualization skills
Work EnvironmentTesting environments, big data platforms like Hadoop, SparkData analysis platforms, BI tools, databases
CertificationsBig Data certifications, ISTQB, testing-focused credentialsData analysis certifications, SQL, Tableau
Industry UsageQuality assurance in big data projectsBusiness insights, reporting, decision-making

Big Data Testing focuses on validating data quality, performance, and integrity within big data systems, requiring testing skills and knowledge of big data tools. Data Analysts interpret and visualize data to support business decisions, emphasizing analytical skills and data visualization. While both roles work with large datasets, Big Data Testing ensures system reliability, whereas Data Analysts focus on deriving insights from data.

What are some common challenges faced by professionals in Big Data Testing, and how can they be addressed?

One common challenge in Big Data Testing is ensuring data quality and accuracy when dealing with vast, complex datasets that often span multiple sources and formats. Testers must also handle performance and scalability issues, as big data platforms process information at high volumes and speeds. Collaborating closely with data engineers and developers is essential to understand data flows and system architecture. To address these challenges, testers often use automation tools, develop robust test strategies, and continually update their skills to keep pace with evolving big data technologies.

What is big data salary?

The salary for a Big Data Testing professional varies based on experience, location, and skill set, but typically ranges from $70,000 to $130,000 annually. Professionals with expertise in tools like Hadoop, Spark, and data validation often command higher salaries, especially in roles requiring advanced technical skills and certifications.

Are QA testers in demand in 2026?

QA testers in big data testing are expected to remain in demand in 2026 due to the increasing volume of data and the need for quality assurance in data pipelines and analytics. Skills in automation tools, scripting, and understanding of data environments will enhance job prospects. Continuous learning and certifications can improve employability in this evolving field.

What are the key skills and qualifications needed to thrive as a Big Data Tester, and why are they important?

To thrive as a Big Data Tester, you need a solid understanding of data analytics, software testing methodologies, and a background in computer science or information technology. Familiarity with big data tools such as Hadoop, Spark, Hive, SQL, as well as automation frameworks and scripting languages like Python or Java, is typically required. Attention to detail, analytical thinking, and strong problem-solving abilities are crucial soft skills for identifying data issues and ensuring data quality. These skills are essential to validate large-scale data systems effectively, ensuring reliability, accuracy, and performance in data-driven projects.

Is big data a good career?

Big Data Testing is a growing field with high demand for professionals skilled in data validation, testing tools, and programming languages like Python or Java. It offers opportunities in industries such as finance, healthcare, and technology, often requiring certifications and knowledge of data management platforms. The career can be lucrative and stable due to the increasing reliance on data-driven decision making.
More about Big Data Testing jobs
What states have the most Big Data Testing jobs? States with the most job openings for Big Data Testing jobs include:
What job categories do people searching Big Data Testing jobs look for? The top searched job categories for Big Data Testing jobs are:
Big Data Testing jobs near you
Infographic showing various Big Data Testing job openings in the United States as of July 2026, with employment types broken down into 2% As Needed, 67% Full Time, 28% Part Time, and 3% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $131,001 per year, or $63 per hour.
QA Engineer (Data)

QA Engineer (Data)

1 point system

Fort Mill, SC • Remote

$30/hr

Contractor

Posted 6 days ago

Job description

Requirement - QA Engineer (Data)

Location- 100% Remote

Contract W2

Rate- $30/hr on W2

we are looking for someone who has tested data pipelines and worked with platforms like Databricks, AWS EMR, or Spark. Some background in PySpark or Hadoop based data testing would be a big plus for us.
A background mostly on the web and mobile automation side, won't be a great right fit for this role.
If you can find someone with It would be great to see candidates with exposure to areas such as Apache Spark testing, EMR/Databricks/Hadoop-based environments, data validation, and other related Big Data testing activities.

Results-driven Senior QA Engineer with 6 to 8+ years of experience specializing in ETL testing, Big Data validation, Apache Spark testing, and Hadoop ecosystem-based quality engineering. Proven expertise in validating large-scale data pipelines across EMR, Databricks, and distributed data processing environments. Strong background in automation testing (UI, API), database testing, and data integrity validation within enterprise applications. Adept at working in Agile environments, collaborating with cross-functional teams, and ensuring high-quality data-driven systems in production. 
Required Skills -

  • 6+ years of software testing experience in quality engineering, quality assurance or a similar role.
  • Bamboo, and Github experience required
  • Cucumber-TestNG framework using JAVA, Selenium, RestAssured, Maven for UI and API Automation Testing experience preferred.
  • Nunit Framework using C#, Selenium, RestAssured, Nugut for UI and API testing experience preferred.
  • Excellent analytical skills with ability to troubleshoot problems and find root causes.
  • It would be great to see candidates with exposure to areas such as Apache Spark testing, EMR/Hadoop-based environments, data validation, and other related Big Data testing activities.
  • Good hands on experience with quality engineering and strategies.
  • Good experience with test automation, database testing, API testing and Java application testing.
  • Experience with use of AI technologies within testing is preferred.


Core Skills

  • Big Data Testing: Apache Spark, Hadoop, EMR, Databricks
  • ETL Testing & Data Validation: Data pipeline validation, transformation testing, reconciliation
  • Automation: Selenium, Cucumber, TestNG, RestAssured, NUnit
  • API Testing: REST APIs, Postman, RestAssured
  • Database Testing: SQL Server, Oracle, Data validation queries
  • Programming: Java, C#, SQL
  • CI/CD: Bamboo, GitHub
  • Frameworks: BDD (Cucumber), TDD
  • Tools: Maven, Jenkins, JIRA


Job Requirements -

  • 6+ years of software testing experience in quality engineering, quality assurance or a similar role mainly in ETL, Data and Hadoop testing.
  • Bamboo, and Github experience required.
  • Good experience with test automation, API testing and Java application testing.
  • Experience with use of AI technologies within testing is preferred.
  • Cucumber-TestNG framework using JAVA, Selenium, RestAssured, Maven for UI and API Automation Testing experience preferred.
  • Nunit Framework using C#, Selenium, RestAssured, Nugut for UI and API testing experience preferred.
  • Excellent analytical skills with ability to troubleshoot problems and find root causes.
  • HealthCare experience pertaining to Medical Claims processing is preferred.
  • Ability to think “outside of the box”.
  • Flexible in thought and creative in approach to testing.
  • Perform end-to-end ETL testing validating large-scale data pipelines across distributed systems.
  • Design and execute Apache Spark testing strategies to validate transformations, aggregations, and streaming pipelines.
  • Conduct data validation and reconciliation testing between source systems, staging layers, and target data warehouses.
  • Work with the Hadoop ecosystem (HDFS, Hive, Spark) for validating batch and real-time data processing.
  • Validate data pipelines deployed on AWS EMR and Databricks environments ensuring data accuracy and completeness.
  • Develop SQL-based validation frameworks to verify data integrity, consistency, and transformation correctness.
  • 4 Year Degree in Computer Science or Management Information Systems or equivalent
  • Perform complex SQL validation for large datasets.
  • Validate data migration and transformation logic across multiple systems.
  • Ensured data quality, completeness, and accuracy through validation rules and checks.